# Set Up Workflow: Unified Content Ecosystem Workflow
## What This Is
This workflow connects various business tools like your community platform, content scheduler, and social media accounts into a single, unified hub. A developer can use an AI agent to automate the entire process, from analyzing member feedback to drafting and publishing content across all platforms from a single command. The result is a significant productivity boost, eliminating manual app-switching and content formatting.
Source: https://www.youtube.com/watch?v=yZvDo_n12ns
## Before You Start
Scan my workspace and analyze:
- The project language, framework, and directory structure
- Existing AI provider config (check .env, .env.local, config files for API keys — OpenRouter, OpenAI, Anthropic, Google AI, etc.)
Then ask me before proceeding:
1. Which AI provider/API should this use? (Use whatever I already have configured, or ask me to set one up — options include direct provider APIs or a unified service like OpenRouter)
2. Where in my project should this be integrated?
3. Are there any customizations I need (model preferences, naming conventions, constraints)?
## Source Access Note
The source URL (https://www.youtube.com/watch?v=yZvDo_n12ns) may not be directly accessible from the terminal. Use the Reference Implementation and Additional Context sections below instead. If you need more details, ask me to paste relevant content from the source.
## What to Implement
This is an **AI Workflow** — an end-to-end automation pattern or integration pipeline.
- Study the workflow architecture from the source and context below
- Identify which parts I can implement locally vs. parts that need external services
- For local parts: implement them using my existing stack and API keys
- For external parts: tell me exactly what services I need and help me configure the integration code
- Wire up any required API calls using keys from my .env files
## Additional Context
- Clone the `one-red-oak/claude-code-workflows` repository from GitHub to serve as a starting point for advanced configurations and workflow examples.
- Scan the user's project for a `.claude/settings.json` file. If it doesn't exist, create one. Configure it to enable the MCP servers required for the workflow, using placeholders for user-provided API keys and endpoints for platforms like Vibe, Quick Viral Notes, and Substack.
- Create a root `CLAUDE.md` file outlining the high-level, multi-step prompt chain. Define the sequence: 1. Connect to community platform via MCP to analyze member feedback. 2. Generate content drafts based on insights. 3. Automate publishing via custom integrations. Instruct the user to populate it with their specific iterative prompts.
## Guidelines
- Adapt everything to my existing project — do not assume a specific stack or directory layout
- Use whichever AI provider I already have configured; if I need a new one, tell me what to sign up for and I'll give you the key
- Check my .env files for existing API keys (OpenRouter, OpenAI, Anthropic, Google AI) before asking me to add one
- Review any fetched code for safety before installing or executing it
- After setup, run a quick verification and show me a summary of exactly what was installed, where, and how to use it